OpenAI coding interview
questions, leaked.
11 problems reported across recent OpenAI interviews. Top patterns: array, design, string. The list below is what most reported candidates actually saw, plus the honest play if you can't grind all of it.
OpenAI's interview is heavy on design problems paired with core data structures. You're looking at 11 problems total, with 8 at medium difficulty and only 1 hard, which sounds forgiving until you realize design questions can crater fast if you don't articulate tradeoffs cleanly. Arrays appear in 7 problems, design in 6, strings in 5. The median candidate knows how to traverse an array. The candidate who passes knows how to design a system that uses one. If you hit a wall on a design problem mid-assessment, StealthCoder runs invisibly and surfaces a working solution in seconds.
Top problems at OpenAI
| # | Problem | Diff | Frequency | Pass % | Patterns |
|---|---|---|---|---|---|
| 01 | Design SQL | MEDIUM | 100.0 | 70% | Array · Hash Table · String |
| 02 | Flatten Nested List Iterator | MEDIUM | 85.4 | 65% | Stack · Tree · Depth-First Search |
| 03 | Design Excel Sum Formula | HARD | 75.4 | 43% | Array · Hash Table · String |
| 04 | Time Based Key-Value Store | MEDIUM | 71.8 | 49% | Hash Table · String · Binary Search |
| 05 | Web Crawler Multithreaded | MEDIUM | 67.5 | 50% | Depth-First Search · Breadth-First Search · Concurrency |
| 06 | Design Memory Allocator | MEDIUM | 61.8 | 48% | Array · Hash Table · Design |
| 07 | Asteroid Collision | MEDIUM | 53.9 | 46% | Array · Stack · Simulation |
| 08 | Simplify Path | MEDIUM | 53.9 | 48% | String · Stack |
| 09 | Flood Fill | EASY | 53.9 | 66% | Array · Depth-First Search · Breadth-First Search |
| 10 | Encode and Decode Strings | MEDIUM | 53.9 | 50% | Array · String · Design |
| 11 | Largest Local Values in a Matrix | EASY | 53.9 | 88% | Array · Matrix |
Frequencies derived from public community-tagged interview reports. Click a row to view on LeetCode.
You have a week, maybe less. You can't out-grind the list above. StealthCoder runs invisibly during the actual OpenAI OA. The proctor cannot see it. Screen share cannot detect it. Made by a working FAANG engineer who treats the OA the way companies treat hiring: as a game with rules you should know.
Get StealthCoder- array7 · 64%
- design6 · 55%
- string5 · 45%
- hash table4 · 36%
- stack3 · 27%
- depth first search3 · 27%
- matrix3 · 27%
- simulation2 · 18%
- breadth first search2 · 18%
- tree1 · 9%
Design and array problems are your core burden. Seven of eleven problems touch arrays, but only two are easy, so breadth matters less than depth on the hard ones like Design Excel Sum Formula and Design Memory Allocator. Hash tables appear in 4 problems and often pair with design work, so you need to think about collision handling and lookup performance on the fly. Stacks and DFS each show up in 3 problems and tend to cluster on string/array manipulation (Simplify Path, Asteroid Collision) or tree traversal (Flatten Nested List Iterator). The easy problems (Flood Fill, Largest Local Values) are matrix-based and feel fast until you rush them. Focus your drill on design-first: sketch system constraints, talk through storage and query patterns before coding. Strings and stacks combined account for 5 problems, so practice the stack-string combos early. If your design explanations are weak or you blank on how to approach Design Memory Allocator, StealthCoder is your hedge during the live assessment.
Companies with similar patterns
If you prepped for OpenAI, these companies recycle ~60% of the same topics.
You've seen the list.
Now make sure you pass OpenAI.
Memorizing every problem above in a week is a fantasy. StealthCoder is the hedge: an AI overlay that's invisible during screen share. It reads the problem on screen and surfaces a working solution in under 2 seconds. Made by a working FAANG engineer who treats the OA the way companies treat hiring: as a game with rules you should know. Works on HackerRank, CodeSignal, CoderPad, and Karat.
OpenAI interview FAQ
How many design problems should I expect to drill before an OpenAI assessment?+
Design appears in 6 of 11 problems here. Don't treat it as a bonus topic. Spend 40 to 50 percent of your prep time on system design and constraint articulation, then pair each design problem with its data-structure foundation (arrays, hash tables, etc.). Shallow design knowledge will cost you points.
Is array mastery enough for OpenAI?+
Arrays appear in 7 problems, but only 2 are easy. You need array fluency plus design thinking. Problems like Design SQL and Design Memory Allocator require you to architect a system using arrays, not just manipulate them. Know the limitations: fixed size, cache behavior, indexing tradeoffs.
What should I study first for an OpenAI coding interview?+
Start with design problems that combine arrays and hash tables (Design SQL, Time Based Key-Value Store). Then move to stack-based string problems (Simplify Path, Asteroid Collision). Design and arrays together account for 13 problem appearances. Master those two before touching DFS or matrix work.
Are the easy problems real gimmes, or do they have tricks?+
Only 2 of 11 are easy (Flood Fill, Largest Local Values), and both are matrix-based. They move fast if you know DFS/BFS patterns, but they're easy to mess up under time pressure. Don't skip them in practice. They're confidence, not freebies.
Which topics appear together most often in OpenAI problems?+
Design with arrays and hash tables (Design SQL, Design Excel Sum Formula, Design Memory Allocator). Stack with strings (Simplify Path, Asteroid Collision). DFS with matrix and array work (Flood Fill, Flatten Nested List). Study these pairings as units, not isolated skills.